Mobile machine with improved machine data authentication

ABSTRACT

An off-road mobile work machine data capture system includes a robustly-identifiable sensor module having a task sensor that provides a task sensor signal indicative of a task. The system also includes a processor coupled to the robustly-identifiable sensor module that is configured to issue a challenge to the robustly-identifiable sensor module and compare a response from the robustly-identifiable sensor module to an expected response to authenticate the robustly-identifiable sensor module. The processor is further configured to generate an indication of authentication failure if the response from the robustly-identifiable sensor module does not match the expected response.

FIELD OF THE DESCRIPTION

The present description generally relates to data acquisition inoff-road machinery. More specifically, but not by limitation, thepresent description relates to authentication of off-road machinerydata.

BACKGROUND

Off-road machinery data acquisition is used in a variety of applicationsto provide data about a process or operation. Such processes oroperations include, without limitation, off-road machinery dataacquisition is in the field of agriculture where data is vitally usefulfor crops, data acquisition is in the field of forestry, constructionequipment, mining equipment, et cetera.

One limitation of current off-road data acquisition is that, in someinstances, the data itself may be spoofed or otherwise acquired ortransmitted in an untrustworthy manner. Spoofed data can lead toerroneous results in a process that relies on such data. One example ofa process that relies on such data is the administration of carboncredits and payments or other activities in furtherance of suchadministration. As can be appreciated, spoofed data indicative of carboncapture could lead to improper payments, regulatory compliance, orcarbon credits based on an erroneous value indicative of carbonsequestration.

Thus, it is becoming more important to provide a system and method toacquire and provide data for off-road machinery such that the data maybe trusted and relied upon.

The discussion above is merely provided for general backgroundinformation and is not intended to be used as an aid in determining thescope of the claimed subject matter.

SUMMARY

A mobile work machine data capture system includes arobustly-identifiable sensor module having a task sensor that provides atask sensor signal indicative of a task. The system also includes aprocessor coupled to the robustly-identifiable sensor module that isconfigured to issue a challenge to the robustly-identifiable sensormodule and compare a response from the robustly-identifiable sensormodule to an expected response to authenticate the robustly-identifiablesensor module. The processor is further configured to generate anindication of authentication failure if the response from therobustly-identifiable sensor module does not match the expectedresponse.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter. The claimed subject matter is not limited to implementationsthat solve any or all disadvantages noted in the background.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagrammatic view of a mobile machine data capture systemoperating in a field in accordance with one embodiment.

FIG. 2 is a flow diagram of a method of acquiring and authenticatingmobile machine data in accordance with one embodiment.

FIG. 3 is a block diagram of a mobile machine data capture system inaccordance with one embodiment.

FIG. 4 is a flow diagram of a method of authenticating a robustlyidentifiable system in accordance with one embodiment.

FIG. 5 is a diagrammatic view of a data capture system operating in asimultaneous mode in accordance with one embodiment.

FIG. 6 is a flow diagram of a method of performing simultaneous machinedata capture in accordance with one embodiment.

FIG. 7 is a flow diagram of a method of performing simultaneous machinedata capture in accordance with one embodiment.

FIG. 8 also depicts another embodiment of a remote server architecture.

FIG. 9 illustrates one example of a computing environment in whichelements of FIGS. 1 and/or 5 , or parts thereof, (for example) can bedeployed.

DETAILED DESCRIPTION

Embodiments described herein generally provide an off-road mobile workmachine with improved data authentication such that data from the mobilework machine may be relied upon for, without limitation, such things aspayments, regulation compliance verification, warranty claims, equipmentdepreciation, et cetera.

FIG. 1 is a diagrammatic view of a mobile machine data capture systemoperating in a field in accordance with one embodiment. In the exampleillustrated in FIG. 1 , mobile machine 1100 is a tractor pulling a tasksensor 1110 through field 1010. In one example, task sensor 1110 isconfigured to include a soil organic matter (SOM) sensor 1012 which isable to provide an indication of soil organic matter as sensor 1012contacts soil in field 1010. In this example, a single element of eachtype is shown for simplicity. In other embodiments, there may be one ormore of such elements. Further, a plurality of such elements may be usedto detect element faults or to implement fault tolerance. In anotherexample, preliminary validation of data could be accomplished by votingthrough mutual interlocking of primary sensors/data collectors. In otherexamples, the plurality of elements may enhance system capabilities suchas task sensors deployed on equipment for per-row data collection.Mobile machine 1100 includes a robustly identifiable processor 1120coupled to a robustly identifiable location/motion module 1130.Location/motion module 1130 is configured to interact with environmentalnavigation signals (such as GPS, global navigation satellite signals,LORAN, or other suitable signals) to provide processor 1120 with anindication of the geographic position of mobile machine 1100.Additionally, mobile machine 1100 includes a wireless transceiver 1140configured to communicate wirelessly with one or more remote devices.Examples of such wireless communication include, without limitation,Bluetooth (such as Bluetooth Specification 2.1 rated at Power Class 2);a Wi-Fi specification (such as IEEE 802.11.a/b/g/n); a known RFIDspecification; cellular communication techniques (such as GSM/CDMA);WiMAX (IEEE 802.16), and/or satellite communication.

Each element of the mobile machine 1100 is termed “robustlyidentifiable” in order to indicate that it may not be copied or clonedfrom the device. In one example, robustly identifiable elements include,for example, a physically unclonable function “PUF.” Thus, the elementcannot be replaced with a substitute or cloned physical replacement or acomputer simulation with the same identifier. In some examples, thereplacement could be used to falsify sensor data values, data location,data timestamp, et cetera prior to being added to a data ledger or storesuch as a block chain record. Further, a robustly identifiable elementis, in one embodiment, packaged in a tamper-evident or tamper-proof wayso that if replacement is attempted, it will not succeed without atleast detection. Finally, a robustly identifiable element is connectedwith other elements in a way which protects the information beingcommunicated. This may include encryption of messages but may alsofurther include how encryption keys are assigned, stored, and managed,to ensure secure data exchange between the elements. By providing anumber of robustly identifiable elements on the mobile machine 1100, theelements above cannot be replaced to spoof georeferenced datacollection. If such an element is replaced, it is done with externalverification, such that the replacement is noted in a trusted way, suchas in an immutable ledger (e.g., block chain record).

FIG. 2 is a flow diagram of a method of acquiring and authenticatingmobile machine data in accordance with one embodiment. Method 2000begins at block 2020 and proceeds to block 2040 for data collection. Thecollected data can include mobile machine data 2060 as well as othersuitable data 2070. An example of machine data 2060 can include thetractor going through the field and collecting data using one or morerobustly identifiable sensors which will be described in greater detailbelow. Next, at block 2030, data protection is performed. In oneembodiment, data protection 2030 is performed using steganography.Steganography is a technique of hiding secret data within an ordinary,non-secret file or message in order to avoid detection. The secret datais then extracted at its destination. The secret data can include theauthentication data. In another example, data protection 2030 is doneusing watermarking. Watermarking is the process of hiding digitalinformation in a carrier signal; the hidden information should, but doesnot need to, contain a relation to the carrier signal. Digitalwatermarks may be used to verify the authenticity or integrity of thecarrier signal or to show the identity of its owners. In some examples,data protection 2030 is done by a secret transformation of valuerepresentations such as encryption/decryption. In some other examples,data values are protected by a secret mapping of value representationpieces to storage locations, such as steganography. These variousexamples of data protection may be used alone or in combination.

Next, at block 2100, the mobile machine performs on-board dataauthentication, which will be described in greater detail below. If theon-board data authentication fails, the mobile machine provides anidentification of such failure and a non-trusted mode is entered. Insuch non-trusted mode, a third party could authenticate data and/orcorroborate and transmit data, as required. However, if on-board dataauthentication is successful, method 2000 moves to on-board datatransmission block 2120. At on-board data transmission block 2120, themobile machine transmits the authenticated data using suitable wirelesscommunication. Such wireless communication is performed using securecommunication techniques, such as cryptography. Finally, at block 2140,method 2000 ends.

FIG. 3 is a block diagram of a mobile machine data capture system inaccordance with one embodiment. System 3000 includes robustlyidentifiable processor 3020. Processor 3020 can include a microprocessoror any other suitable integrated circuitry that is capable of performinginstructions to provide authentication. In one example, processor 3020includes or is coupled to a source 3024 of challenge/response code.Challenge/response code 3024 can include instructions that causeprocessor 3020 cause or command processor 3020 to issue a challenge to arobustly-identifiable system as well as instructions to compare therobustly identifiable system's response to the challenge with anexpected response. Further, challenge/response code 3024 may alsoinclude code to allow processor 3020 to access its own physicallyunclonable function module 3026 and compare a response with an expectedresponse. In this way, processor 3020 can determine whether it, itself,is an authentic processor, or one that has been replaced.

As processor 3020 issues challenges to each robustly-identifiablesystem, and receives responses, processor 3020 determines whether eachrobustly identifiable system is authenticated. As shown in FIG. 3 , afirst robustly-identifiable system is indicated at sensor module 3040which includes, or is coupled to, one or more task sensors 3060, such asa soil organic matter sensor, or other suitable sensor as well as aphysically unclonable function (PUF) module 3080. When sensor module3040 receives a challenge from processor 3020 via communication line3100, sensor module 3040 employs physically unclonable function module3080 to provide its response. In some examples, the response may bededicated strictly to responding to the challenge. In other examples,the response may be part of a message which incorporates other data froma module.

A physically unclonable function is generally a physical object that,for a given input and conditions (i.e., challenge), provides aphysically-defined “digital fingerprint” output (response) that servesas a unique identifier. Physically unclonable functions are sometimesbased on unique physical variations that occur naturally duringsemiconductor manufacturing. A physical unclonable function is aphysical entity embodied in a physical structure. Physical unclonablefunctions are available in integrated circuits, and are sometimes usedin applications with high security requirements, such as cryptography.

System 3000 also includes a robustly-identifiable location/motion module3120. Location/motion module 3120 includes one or more location/motionsensors 3140 as well as location/motion physically unclonable functionmodule 3160. Location/motion sensors 3140 can include geographiclocation sensors, such as GPS, GLONASS (Russia), Galileo (EU), BeiDou.and/or fixed LORAN. Further, motion sensors can include suitableinertial measurement units, accelerometers, gyroscopes, or any suitablesensor that provides an indication relative to motion of the mobilemachine. Location/motion module 3120 is coupled to a digitalcommunication line 3180 in order to receive a challenge from processor3020. When such challenge is received, module 3120 accesseslocation/motion physically unclonable function module 3160 to provide aresponse.

Robustly identifiable communication module 3200 is coupled to processor3020 and includes one or more wireless transceivers 3240. Additionally,robustly identifiable communication module 3200 includes communicationmodule physical unclonable function 3260. Communication module 3200 isconfigured to receive a challenge from robustly identifiable processor3020 via communication line 3220 and provide a response based oncommunication module physical unclonable function 3260.

While each of robustly identifiable modules 3040, 3120, and 3200, areillustrated as being coupled to robustly identifiable processor 3020 viarespective communication lines 3100, 3180, and 3220, it is expresslycontemplated that all such robustly identifiable modules could becoupled to robustly identifiable processor 3020 via a singlecommunication line or bus. Any of processor 3020 and robustlyidentifiable modules 3040, 3120, and 3200 may be in separate enclosuresor shared enclosures. The enclosures may include physical tamper-prooffeatures.

FIG. 4 is a flow diagram of a method of authenticating arobustly-identifiable system in accordance with one embodiment. Thisexample is hierarchical with processor 3020 as lead. In other examples,other components may take the lead. In still other examples, a peer,hybrid peer/hierarchical or other architectures may be used as well.Method 4000 begins at block 4020 where a processor, such as processor3020, initializes. During such initialization, the processor may checkits own robustly-identifiable function, such as challenging andcomparing its own response utilizing a physically unclonable function,as described above. This is indicated generally at block 4040.Additionally, other suitable techniques that generate a uniquelyidentifiable response based upon a challenge can be used, as indicatedat block 4060. Regardless of the technique, upon completion ofinitialization block 4020, the processor or other suitable controlcircuitry of the robustly identifiable system can determine whether itis an authenticated physical device. In the event that the processor isunable to authenticate itself, method 4000 proceeds to failsafe block4120 as indicated at reference numeral 4030.

Next, control passes to block 4080 where the authenticated processorissues a challenge to a robustly-identifiable sensor module. Forexample, the authenticated processor may issue a challenge over acommunication line, such as line 3100, to a sensor module having arobustly identifiable aspect, such as a physically unclonable functionmodule 3080. The authenticated processor then receives a response fromthe robustly-identifiable sensor module and compares the receivedresponse with an expected response known by the authenticated processor.If the received response matches the expected response, control passesto block 4100. However, if the received response does not match theexpected response, indicating failure in authentication of the sensormodule, control passes to failsafe block 4120 via line 4140.

Next, at block 4100, the authenticated processor issues anauthentication challenge to a robustly-identifiable location/movementmodule, such as module 3120. If the location/motion module issues thecorrect response, method 4000 proceeds to block 4160. However, if thelocation/movement module fails to issue the expected response to thechallenge, then control passes to failsafe block 4120 via line 4180.

Next, at block 4160, the authenticated processor issues a challenge to acommunication module, such as communication module 3200. In response,the communication module accesses its own robustly-identifiableindicator or physically unclonable function and provides a response tothe challenge. If the response to the challenge is the expectedresponse, method 4000 proceeds to block 4200 where trusted operation isinitiated. During trusted operation, all data acquired and stored can beconsidered as trusted data. However, if the response of thecommunication module to the challenge does not match the expectedresponse, control passes to failsafe module 4120 via line 4220.

At fail safe module 4120, data acquisition and capture can still occur.However, the processor will provide an indication that authenticationfailed such that an appropriate level of trust and/or externalauthentication/corroboration can be performed.

FIG. 5 is a diagrammatic view of a data capture system operating in asimultaneous mode in accordance with one embodiment. The simultaneousmode illustrates an additional level of authenticity that may be addedby independent confirmation of field activity such as the soil organicmatter (SOM) data collection. This confirmation could, in someembodiments, become part of a distributed immutable ledger. Thesimultaneous mode illustrated with respect to FIG. 5 can be performedupon authentication failure with respect to the method described withrespect to FIG. 4 . However, simultaneous mode can also be performed inorder to provide additional authenticity even when the authenticationdescribed with respect to FIG. 4 is completed successfully.

As shown in FIG. 5 , three independent soil organic matter measuresurveys are being performed. They may be occurring simultaneously orseparated in time. A terrestrial sensor system 5100 (illustrateddiagrammatically as a mobile machine-tractor) similar to the onedescribed with respect to FIG. 1 , collects georeferenced soil organicmatter data from task sensor 5110 and sends it via transceiver 5140 oversecure communications link 5150 to receiver 5170 for storage on secureserver 5180.

FIG. 5 also illustrates an aerial sensor system (illustrateddiagrammatically as an unmanned aerial vehicle) 5200 collectinggeoreferenced soil organic matter data from task sensor 5210 and sendingit via transceiver 5240 over secure communications link 5250 to receiver5270 for storage on secure server 5280. Aerial sensor system 5200 mayhave a pole, UAV, manned aircraft, satellite, et cetera, as a sensorplatform.

Similarly, a manual sensor system 5300 collects georeferenced soilorganic matter data from task sensor 5310 and sends it via transceiver5340 over secure communications link 5350 to receiver 5370 for storageon secure server 5380.

Secure servers 5180, 5280, and 5380 are connected by a secure network5400. The authentic georeferenced data collected by task sensors 5110,5210, and 5310 may be combined and stored or otherwise persisted in adistributed, immutable ledger, such as a blockchain.

The distributed, immutable ledger may be used to document the amount ofcarbon or any other suitable chemical sequestered in the soil, forexample. Surveys taken at a plurality of times may be used to documentthe change in sequestered carbon over time. This measured difference maybe used to establish premiums, payments, and penalties. In one SOMexample, mobile machine 5100 may be a farmer-owned tractor, aerialsensor system 5200 may be a USDA-owned drone, and manual sensor system5300 may be a carbon exchange auditor point probe.

The measured values and trends may be used to guide farming practicessuch as tillage location, type, and depth. Further, the measured valuesmay be used to guide planting and seeding depths, crop care chemicalselection and prescription, and harvest residue management.

FIG. 6 is a flow diagram of a method of performing simultaneous machinedata capture in accordance with one embodiment. Method 6000 begins atblock 6020 and proceeds to block 6040 where data collection occurs. Thisdata collection can include machine data 6060 as well as on any othersuitable data, as indicated at block 6070. Next, method 6000 proceeds toblock 6080 where data watermarking is performed. Once the datawatermarking is performed, flow splits with processing occurring at bothon-board data authentication block 6100 as well as third-party dataauthentication block 6160. On-board data authentication 6100 isgenerally performed with respect to the mobile machine, such as atractor. Further, this block 6100 can include the steps or blockdescribed with respect to FIG. 4 .

Third-party data authentication block 6160 occurs where one or morethird-parties authenticate or corroborate data captured by the machine.This authentication could be performed as set forth above, with respectto robustly-identifiable systems. However, the third-partyauthentication could also be performed in other ways. In the most secureembodiments, all third-parties will also check to see if their owncomponents are expected using the robustly-identifiable techniquesdescribed above.

At block 6120, the mobile machine transmits its acquired machine dataregardless of whether the authentication for the on-board data wassuccessful. However, in the event that the on-board data authenticationat block 6100 was not successful, the on-board data transmission block6120 will include an indication of failure of such authentication.

Turning to block 6180, the third-party data transmission occurs. Thedata from the on-board data transmission as well as the third-party datatransmission is then compared to make sure there are no discrepancies orthat any discrepancies are within a margin of error. The margin can bespecified depending on the type of transaction or operation beingperformed. Further, the actual provided data relative to the operationcan be interpolated based on the on-board data transmission and thethird-party data transmission. The final processed or interpolated datawith respect to the operation may then be stored in an immutable ledger,such as using a blockchain. Further, the communication with theimmutable ledger is preferably encrypted. These ledgers are generallyaccessed for read publicly and for write in an authenticated manner. Theledger's data cannot be altered (i.e. immutable). The communication withthe immutable ledger is signed or otherwise authenticated to uniquelyidentify the entity communicating with the ledger, but the communicationdoes not necessarily need to be encrypted.

FIG. 7 is a flow diagram of a method of performing simultaneous machinedata capture in accordance with one embodiment. Method 7000 is similarto method 6000 and like components are numbered similarly. As can beseen, method 7000 includes an explicit data comparison step at block7020 which determines whether the data from the on-board transmissionblock 6120 and the third-party data transmission block 6180 arediscrepant. If the data are not discrepant, control passes to block 7060where method 7000 ends by using the non-discrepant data. However, ifblock 7020 determines that the data is discrepant, or discrepant beyonda selected threshold (such as 5% or 10%) method 7000 generates adeviation signal at block 7040 indicating that the data discrepancy,which can allow those who reply upon the mobile machine's data toascribe less trust or confidence in the data for critical decisions.

While embodiments described thus far have generally described a soilorganic matter sensor, this is for illustration purposes only. It isexpressly contemplated that embodiments described herein are applicableto any type of data acquisition with respect to any mobile machine wheredata authentication is important. Examples of other operations orindustries where such data authentication is important include, withoutlimitation, forestry, soil compaction, chemical application, tillage,planting/seeding, organic practices, and carbon sequestration. Forexample, cut-to-length timber harvesters have sensors for measuring treelength and diameter. The sensors have been proposed for measuring wooddensity. Such sensors could replace the soil organic matter sensordescribed above and provide an authenticated manner for capturing datawith respect to wood volume being removed from a forest. Such data couldbe used to estimate the amount of carbon being removed from the forestin the form of wood.

In another example, referring to FIG. 1 , the mobile machine couldinstead be a construction soil compactor which comprises a compactiondrum with a compaction sensor in addition to a task processor,location/motion sensor, transceiver, and network. Rather than measuringsoil organic matter, the construction soil compactor compacts soil for aroad bed. The compaction level must meet a contractual or projectspecification prior to, for example, putting a layer of concrete overthe bed as a road. In FIG. 5 , modifications to machine 5100 could carryover from the above description of FIG. 1 . Soil compaction data wouldbe collected by a sub-contractor machine. Human 5340, a Department ofTransportation employee, may use a cone penetrometer to obtain soilcompaction data. Drone 5200 may be owned and operator by the contractorwho is monitoring work of the sub-contractor machine. Authenticated datafrom the three sources may be combined into a distributed immutableledger, such as a blockchain-like distributed, immutable ledger toprovide a record of operations occurring on the worksite.

The present discussion has mentioned processors and servers. In oneembodiment, the processors and servers include computer processors withassociated memory and timing circuitry, not separately shown. They arefunctional parts of the systems or devices to which they belong and areactivated by, and facilitate the functionality of the other componentsor items in those systems. Example implementations of the invention mayuse one or more processors. In multi-processor implementations, theprocessors may be local, remote, or a mixture. The processors may shareinformation via wired, wireless, or a mixture of such communicationstechniques. Further, in multi-processor embodiments, portions ofcomputations may be fixedly or dynamically assigned to differentprocessors.

A number of data stores have also been discussed. It will be noted theycan each be broken into multiple data stores. All can be local to thesystems accessing them, all can be remote, or some can be local whileothers are remote. All of these configurations are contemplated herein.

Also, the figures show a number of blocks with functionality ascribed toeach block. It will be noted that fewer blocks can be used so thefunctionality is performed by fewer components. Also, more blocks can beused with the functionality distributed among more components.

FIG. 8 a block diagram of mobile machine 1000, shown in FIG. 1 , exceptthat it communicates with elements in a remote server architecture 500.In an example embodiment, remote server architecture 500 can providecomputation, software, data access, and storage services that do notrequire end-user knowledge of the physical location or configuration ofthe system that delivers the services. In various embodiments, remoteservers can deliver the services over a wide area network, such as theinternet, using appropriate protocols. For instance, remote servers candeliver applications over a wide area network and they can be accessedthrough a web browser or any other computing component. Software orcomponents shown in FIG. 1 as well as the corresponding data, can bestored on servers at a remote location. The computing resources in aremote server environment can be consolidated at a remote data centerlocation or they can be dispersed. Remote server infrastructures candeliver services through shared data centers, even though they appear asa single point of access for the user. Thus, the components andfunctions described herein can be provided from a remote server at aremote location using a remote server architecture. Alternatively, theycan be provided from a conventional server, or they can be installed onclient devices directly, or in other ways.

In the embodiment shown in FIG. 8 , some items are similar to thoseshown in FIG. 5 and they are similarly numbered. FIG. 8 specificallyshows servers 5180, 5280, and 5380 can be located at a remote serverlocation 502. Therefore, mobile machine 1000 accesses those systemsthrough remote server location 502.

FIG. 8 also depicts another embodiment of a remote server architecture.FIG. 8 shows that it is also contemplated that some elements aredisposed at remote server location 502 while others are not. By way ofexample, remote storage 120 can be disposed at a location separate fromlocation 502 and accessed through the remote server at location 502.Regardless of where they are located, they can be accessed directly bymobile machine 1000, through a network (either a wide area network or alocal area network), they can be hosted at a remote site by a service,or they can be provided as a service, or accessed by a connectionservice that resides in a remote location. Also, the data can be storedin substantially any location and intermittently accessed by, orforwarded to, interested parties.

FIG. 9 illustrates one example of a computing environment in whichelements of FIGS. 1 and/or 5 , or parts thereof, (for example) can bedeployed. With reference to FIG. 9 , an exemplary system forimplementing some embodiments includes a general-purpose computingdevice in the form of a computer 810. Components of computer 810 mayinclude, but are not limited to, a processing unit 820 (which cancomprise processor 108), a system memory 830, and a system bus 821 thatcouples various system components including the system memory to theprocessing unit 820. The system bus 821 may be any of several types ofbus structures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures.Memory, programs and/or code described with respect to FIGS. 1, 3 and/or5 can be deployed in corresponding portions of FIG. 9 .

Computer 810 typically includes a variety of computer readable media.Computer readable media can be any available media that can be accessedby computer 810 and includes both volatile and nonvolatile media,removable and non-removable media. By way of example, and notlimitation, computer readable media may comprise computer storage mediaand communication media. Computer storage media is different from, anddoes not include, a modulated data signal or carrier wave. It includeshardware storage media including both volatile and nonvolatile,removable and non-removable media implemented in any method ortechnology for storage of information such as computer readableinstructions, data structures, program modules or other data. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical disk storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othermedium which can be used to store the desired information and which canbe accessed by computer 810. Communication media may embody computerreadable instructions, data structures, program modules or other data ina transport mechanism and includes any information delivery media. Theterm “modulated data signal” means a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal.

The system memory 830 includes computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) 831and random access memory (RAM) 832. A basic input/output system 833(BIOS), containing the basic routines that help to transfer informationbetween elements within computer 810, such as during start-up, istypically stored in ROM 831. RAM 832 typically contains data and/orprogram modules that are immediately accessible to and/or presentlybeing operated on by processing unit 820. By way of example, and notlimitation, FIG. 9 illustrates operating system 834, applicationprograms 835, other program modules 836, and program data 837.

The computer 810 may also include other removable/non-removablevolatile/nonvolatile computer storage media. By way of example only,FIG. 9 illustrates a hard disk drive 841 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 851,nonvolatile magnetic disk 852, an optical disk drive 855, andnonvolatile optical disk 856. The hard disk drive 841 is typicallyconnected to the system bus 821 through a non-removable memory interfacesuch as interface 840, and magnetic disk drive 851 and optical diskdrive 855 are typically connected to the system bus 821 by a removablememory interface, such as interface 850.

Alternatively, or in addition, the functionality described herein can beperformed, at least in part, by one or more hardware logic components.For example, and without limitation, illustrative types of hardwarelogic components that can be used include Field-programmable Gate Arrays(FPGAs), Program-specific Integrated Circuits (e.g., ASICs),Program-specific Standard Products (e.g., ASSPs), System-on-a-chipsystems (SOCs), Complex Programmable Logic Devices (CPLDs), etc.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 9 , provide storage of computer readableinstructions, data structures, program modules and other data for thecomputer 810. In FIG. 9 , for example, hard disk drive 841 isillustrated as storing operating system 844, application programs 845,other program modules 846, and program data 847. Note that thesecomponents can either be the same as or different from operating system834, application programs 835, other program modules 836, and programdata 837.

A user may enter commands and information into the computer 810 throughinput devices such as a keyboard 862, a microphone 863, and a pointingdevice 861, such as a mouse, trackball or touch pad. Other input devices(not shown) may include a joystick, game pad, satellite dish, scanner,or the like. These and other input devices are often connected to theprocessing unit 820 through a user input interface 860 that is coupledto the system bus, but may be connected by other interface and busstructures. A visual display 891 or other type of display device is alsoconnected to the system bus 821 via an interface, such as a videointerface 890. In addition to the monitor, computers may also includeother peripheral output devices such as speakers 897 and printer 896,which may be connected through an output peripheral interface 895.

The computer 810 is operated in a networked environment using logicalconnections (such as a local area network—LAN, or wide area network WAN)to one or more remote computers, such as a remote computer 880.

When used in a LAN networking environment, the computer 810 is connectedto the LAN 871 through a network interface or adapter 870. When used ina WAN networking environment, the computer 810 typically includes amodem 872 or other means for establishing communications over the WAN873, such as the Internet. In a networked environment, program modulesmay be stored in a remote memory storage device. FIG. 9 illustrates, forexample, that remote application programs 885 can reside on remotecomputer 880.

It should also be noted that the different embodiments described hereincan be combined in different ways. That is, parts of one or moreembodiments can be combined with parts of one or more other embodiments.All of this is contemplated herein.

Example 1 is a mobile work machine data capture system comprising: arobustly-identifiable sensor module having a task sensor that provides atask sensor signal indicative of a task; and a processor coupled to therobustly-identifiable sensor module, the processor being configured toissue a challenge to the robustly-identifiable sensor module and comparea response from the robustly-identifiable sensor module to an expectedresponse to authenticate the robustly-identifiable sensor module, theprocessor being further configured to generate an indication ofauthentication failure if the response from the robustly-identifiablesensor module does not match the expected response.

Example 2 is the mobile work machine data capture system of any or allprevious examples, wherein the robustly-identifiable sensor moduleincludes a physically unclonable function module and wherein theresponse from the robustly-identifiable sensor module is based on acharacteristic of the physically unclonable function module.

Example 3 is the mobile work machine data capture system of any or allprevious examples, wherein the task sensor is a soil organic mattersensor.

Example 4 is the mobile work machine data capture system of any or allprevious examples, wherein the task sensor is a soil compaction sensor.

Example 5 is the mobile work machine data capture system of any or allprevious examples, and further comprising a first robustly-identifiableidentifiable location/motion module coupled to the processor, theprocessor being configured to issue a challenge to the firstrobustly-identifiable location/motion module and compare a response fromthe first robustly-identifiable location/motion module to an expectedresponse to authenticate the first robustly-identifiable location/motionmodule, the processor being further configured to generate an indicationof authentication failure if the response from the firstrobustly-identifiable location/motion module does not match the expectedresponse.

Example 6 is the mobile work machine data capture system of any or allprevious examples, wherein the location/motion module includes a GPSreceiver.

Example 7 is the mobile work machine data capture system of any or allprevious examples, wherein the location/motion module includes aninertial measurement unit.

Example 8 is the mobile work machine data capture system of any or allprevious examples, wherein the location/motion module includes aphysically unclonable function module and wherein the response from therobustly-identifiable location/motion module is based on acharacteristic of the physically unclonable function module.

Example 9 is the mobile work machine data capture system of any or allprevious examples, and further comprising a second robustly-identifiableidentifiable location/motion module coupled to the processor, theprocessor being configured to issue a challenge to the secondrobustly-identifiable location/motion module and compare a response fromthe second robustly-identifiable location/motion module to an expectedresponse to authenticate the second robustly-identifiablelocation/motion module, the processor being further configured togenerate an indication of authentication failure if the response fromthe second robustly-identifiable location/motion module does not matchthe expected response.

Example 10 is the mobile work machine data capture system of any or allprevious examples, wherein the processor is a robustly-identifiableprocessor.

Example 11 is the mobile work machine data capture system of any or allprevious examples, wherein the robustly-identifiable processor isconfigured to employ a processor physically unclonable function toauthenticate the processor.

Example 12 is the mobile work machine data capture system of any or allprevious examples, wherein and further comprising arobustly-identifiable identifiable wireless communication module coupledto the processor, the processor being configured to issue a challenge tothe robustly-identifiable wireless communication module and compare aresponse from the robustly-identifiable wireless communication module toan expected response to authenticate the robustly-identifiable wirelesscommunication module, the processor being further configured to generatean indication of authentication failure if the response from therobustly-identifiable wireless communication module does not match theexpected response.

Example 13 is the mobile work machine data capture system of any or allprevious examples, wherein the robustly-identifiable wirelesscommunication module includes a physically unclonable function moduleand wherein the response from the robustly-identifiable wirelesscommunication module is based on a characteristic of the physicallyunclonable function module.

Example 14 is the mobile work machine data capture system of any or allprevious examples, wherein the robustly-identifiable wirelesscommunication module is configured to securely communicate with a remotedevice.

Example 15 is the mobile work machine data capture system of any or allprevious examples, wherein the secure communication includescryptographic communication.

Example 16 is a system for authenticating data of a mobile work machine.The system includes a remote computer system; a first data capturesystem mounted to an off-road mobile machine, the first data capturesystem comprising: a robustly-identifiable sensor module having a tasksensor that provides a task sensor signal indicative of a task; awireless communication module; and a processor coupled to therobustly-identifiable sensor module and the communication module, theprocessor being configured to acquire data from the task sensor signaland transmit the acquired data to the remote computer system using thewireless communication module; and a second data capture system disposedto capture additional data relative to operation of the mobile machineand transmit the additional data to the remote computer system; andwherein the remote computer system is configured to receive the acquireddata from the first data capture system and to receive the additionaldata from the second data capture system and combine the acquired dataand the additional data to generate combined data and wherein the remotecomputer system is configured to store the combined data in an immutableledger.

Example 17 is the system of any or all previous examples, wherein theimmutable ledger is a distributed, immutable ledger that employsblockchain.

Example 18 is the system of any or all previous examples, wherein thesecond data capture system captures data relative to at least one oflocation, time, and actions of the mobile machine.

Example 19 is the system of any or all previous examples, wherein theremote computer system is configured to compare the acquired data withthe additional data and generate a deviation signal if there is adiscrepancy exceeding a pre-selected threshold.

Example 20 is a data capture system for a mobile machine. The datacapture system comprises at least one robustly-identifiable task sensor;at least one robustly-identifiably processor coupled to the at least onerobustly-identifiable task sensor; at least one robustly-identifiablelocation/motion module coupled to the at least one robustly-identifiableprocessor and configured to provide an indication of at least one ofgeographic location and relative machine motion; at least onerobustly-identifiable wireless transceiver operably coupled to the atleast one robustly-identifiable processor and configured to securelycommunicate with a remote device.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims.

What is claimed is:
 1. A mobile work machine comprising: arobustly-identifiable sensor module having a task sensor that provides atask sensor signal indicative of a task; and a processor communicativelycoupled to the robustly-identifiable sensor module, the processor beingconfigured to issue a challenge to the robustly-identifiable sensormodule and compare a response from the robustly-identifiable sensormodule to an expected response to authenticate the robustly-identifiablesensor module, the processor being further configured to generate anindication of authentication failure if the response from therobustly-identifiable sensor module does not match the expectedresponse.
 2. The mobile work machine of claim 1, wherein therobustly-identifiable sensor module includes a physically unclonablefunction module and wherein the response from the robustly-identifiablesensor module is based on a characteristic of the physically unclonablefunction module.
 3. The mobile work machine of claim 1, wherein the tasksensor is a soil organic matter sensor.
 4. The mobile work machine ofclaim 1, wherein the task sensor is configured to provide an indicationof accumulated hours of operation.
 5. The mobile work machine of claim1, and further comprising a first robustly-identifiable location/motionmodule coupled to the processor, the processor being configured to issuea challenge to the first robustly-identifiable location/motion moduleand compare a response from the first robustly-identifiablelocation/motion module to an expected response to authenticate the firstrobustly-identifiable location/motion module, the processor beingfurther configured to generate an indication of authentication failureif the response from the first robustly-identifiable location/motionmodule does not match the expected response.
 6. The mobile work machineof claim 5, wherein the first robustly-identifiable location/motionmodule includes a GPS receiver.
 7. The mobile work machine of claim 5,wherein the first robustly-identifiable location/motion module includesan inertial measurement unit.
 8. The mobile work machine of claim 5,wherein the first robustly-identifiable location/motion module includesa physically unclonable function module and wherein the response fromthe first robustly-identifiable location/motion module is based on acharacteristic of the physically unclonable function module.
 9. Themobile work machine of claim 5, and further comprising a secondrobustly-identifiable location/motion module coupled to the processor,the processor being configured to issue a challenge to the secondrobustly-identifiable location/motion module and compare a response fromthe second robustly-identifiable location/motion module to an expectedresponse to authenticate the second robustly-identifiablelocation/motion module, the processor being further configured togenerate an indication of authentication failure if the response fromthe second robustly-identifiable location/motion module does not matchthe expected response.
 10. The mobile work machine of claim 1, whereinthe processor is a robustly-identifiable processor.
 11. The mobile workmachine of claim 10, wherein the robustly-identifiable processor isconfigured to employ a processor physically unclonable function toauthenticate the processor.
 12. The mobile work machine of claim 1, andfurther comprising a robustly-identifiable identifiable wirelesscommunication module coupled to the processor, the processor beingconfigured to issue a challenge to the robustly-identifiable wirelesscommunication module and compare a response from therobustly-identifiable wireless communication module to an expectedresponse to authenticate the robustly-identifiable wirelesscommunication module, the processor being further configured to generatean indication of authentication failure if the response from therobustly-identifiable wireless communication module does not match theexpected response.
 13. The mobile work machine of claim 12, wherein therobustly-identifiable wireless communication module includes aphysically unclonable function module and wherein the response from therobustly-identifiable wireless communication module is based on acharacteristic of the physically unclonable function module.
 14. Themobile work machine of claim 12, wherein the robustly-identifiablewireless communication module is configured to securely communicate witha remote device.
 15. The mobile work machine of claim 14, wherein thesecure communication includes cryptographic communication.
 16. A systemfor authenticating data of a mobile work machine, the system comprising:a remote computer system; a first data capture system mounted to anoff-road mobile machine, the first data capture system comprising: arobustly-identifiable sensor module having a task sensor that provides atask sensor signal indicative of a task; a wireless communicationmodule; and a processor coupled to the robustly-identifiable sensormodule and the communication module, the processor being configured toacquire data from the task sensor signal and transmit the acquired datato the remote computer system using the wireless communication module;and a second data capture system disposed to capture additional datarelative to operation of the mobile machine and transmit the additionaldata to the remote computer system; and wherein the remote computersystem is configured to receive the acquired data from the first datacapture system and to receive the additional data from the second datacapture system and combine the acquired data and the additional data togenerate combined data and wherein the remote computer system isconfigured to store the combined data in an immutable ledger.
 17. Thesystem of claim 16, wherein the immutable ledger is a distributed,immutable ledger that employs blockchain.
 18. The system of claim 16,wherein the second data capture system captures data relative to atleast one of location, time, and actions of the mobile machine.
 19. Thesystem of claim 16, wherein the remote computer system is configured tocompare the acquired data with the additional data and generate adeviation signal if there is a discrepancy exceeding a pre-selectedthreshold.
 20. A data capture system for a mobile machine, the datacapture system comprising: at least one robustly-identifiable tasksensor; at least one robustly-identifiably processor coupled to the atleast one robustly- identifiable task sensor; at least onerobustly-identifiable location/motion module coupled to the at least onerobustly-identifiable processor and configured to provide an indicationof at least one of geographic location and relative machine motion; atleast one robustly-identifiable wireless transceiver operably coupled tothe at least one robustly-identifiable processor and configured tosecurely communicate with a remote device.